Image processing device and method thereof

ABSTRACT

Volume data is used for extracting a contour of a measurement object and measurement information describing anatomical structure useful for diagnosis is acquired from the contour. When volume data of a subject is inputted (S301), an image processing device detects feature points in the volume data (S302); detects contours of a plurality of parts in the volume data based on the detected feature points and anatomical definitions (S303); and optimizes boundary lines defining contours of parts contacting each other, out of the detected plural parts, so as to combine together the optimized contours of the plural parts for creating a contour of the measurement object (S304). Measurements are taken on diagnostic items useful for diagnosis based on the created contour (S305); and the acquired measurement information is outputted as measurement results (S306) which are displayed at a display.

TECHNICAL FIELD

The present invention relates to an image processing device and moreparticularly, to an image processing technique that acquires measurementinformation for diagnostic use by extracting a contour of a measurementobject from three-dimensional information.

BACKGROUND ART

Ultrasonic systems such as ultrasonic diagnostic equipment have acharacteristic of enabling the observation of the inside of a subjectwithout destroying the subject. Particularly in the medical field, theultrasonic systems negate the need for surgical operations such aslaparotomy for treatment of human body and hence, have found wideranging applications as means for providing safe observation of internalorgans. The heart is one of the subjects of the ultrasonic systems. Withthe advent of the aging society, the recent years have seen the increasein the number of people suffering cardiac valvular diseases such asmitral regurgitation. Valvuloplasty, valve-sparing surgery and the likehave been widely performed as a method of treatment of the cardiacvalvular diseases. For the sake of achieving success in the surgery, anexact diagnosis of the disease based on echocardiographic examinationmust be done before surgery.

In a conventional practice, an examiner as a user acquires as followsmeasurement information pieces, such as annulus diameter, valve heightand valvular area, which are necessary for making a diagnosis. Namely,the examiner captures two-dimensional echocardiographic images andmanually extracts a contour of the cardiac valve while watching thecross-sectional images. Unfortunately, the manual operations ofextracting the cardiac valve contour and taking measurements of variousdiagnostic items involve complicated processes and take much time. It isalso difficult to clarify a complicated three-dimensional structure suchas of the cardiac valve by using the two-dimensional sectional images.More recently, a system has been provided which uses a specialultrasonic probe for acquiring volume data or three-dimensionalinformation such as stereoscopic ultrasonic image of heart. The systemautomatically acquires measurement information for diagnosis from thevolume data.

Patent Literature 1 is cited as an example of the related prior artdocuments. The technique of Patent Literature 1 is for acquisition ofclinically required information such as annulus area, height and thelike of the cardiac mitral valve. For acquisition of a three-dimensionalimage of the cardiac valve, a three-dimensional echocardiography imageis generated from a two-dimensional echocardiography images obtained byscanning with an echocardiographic machine. Namely, the patentliterature relates to a method of automatically extracting thethree-dimensional cardiac valve image through computer processing, wherethe three-dimensional cardiac valve image providing for the measurementof clinically required data is automatically extracted by optimizing afitting evaluation function (potential energy) of an annulus model in afitting model considering the physical shapes of the heart and theannulus by means of a replica exchange method/expansion slow coolingmethod.

CITATION LIST Patent Literature

PTL 1: International Publication No. WO2006/068271

SUMMARY OF INVENTION Technical Problem

According to Patent Literature 1, the contour of the cardiac valve asregarded as one shape is extracted from the volume data. However, theobject of measurement such as the cardiac valve has such a complicatedshape that it is never easy to extract the whole contour of the subjectat one stroke and with a high degree of precisions. It is reported thatthe cardiac valve includes therein a plurality of parts based onanatomical definitions, every one of which is useful for diagnosis ofdisease. It is therefore necessary to extract not only the whole contourof the measurement object but also boundary lines between the partswhich define an internal structure. However, Patent Literature 1 doesnot disclose a method for extracting the boundary lines between theparts of the measurement object.

Accordingly, it is an object of the invention to provide an imageprocessing device capable of extracting the contour of the measurementobject with high precisions and measurement information necessary fordiagnosis of the measurement object as well as a method thereof, whichaddress the above-described problem.

Solution to Problem

According to an aspect of the invention for achieving the above object,an image processing device including a processor has an arrangementwherein the processor detects feature points in volume data of ameasurement object; extracts contours of a plurality of parts of themeasurement object based on the detected feature points and anatomicaldefinitions; optimizes the contours of parts contacting each other, outof the extracted contours of the plural parts, so as to combine togetherthe plural parts for creating a contour of the measurement object; andacquires measurement information therefrom.

According to another aspect of the invention for achieving the aboveobject, an image processing method of an image processing device has anarrangement wherein the image processing device detects feature pointsin volume data of a measurement object; extracts contours of a pluralityof parts of the measurement object based on the detected feature pointsand anatomical definitions; optimizes the contours of parts contactingeach other, out of the extracted contours of the plural parts, so as tocombine together the plural parts for creating a contour of themeasurement object; and acquires measurement information therefrom.

Advantageous Effects of Invention

According to the invention, the high-precision contour and measurementinformation of the measurement object can be acquired.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram showing an example of the whole structure ofan ultrasonic imaging system according to Example 1 of the invention.

FIG. 2 is a block diagram showing an example of a hardware configurationof the ultrasonic imaging system according to Example 1 hereof.

FIG. 3 is a flow chart showing an example of a processing flow ofmeasurement of cardiac valve according to Example 1 hereof.

FIG. 4 is a schematic diagram showing an example of feature pointsetting according to Example 1 hereof.

FIG. 5 is a schematic diagram showing an example of creating contours ofplural parts from a cardiac mitral valve according to Example 1 hereof.

FIG. 6 is a schematic diagram showing an example of extracting a contourof a part according to Example 1 hereof.

FIG. 7 is a schematic diagram showing an example of boundary lineoptimization according to Example 1 hereof.

FIG. 8 is a schematic diagram showing an example of display of boundaryline modification according to Example 1 hereof.

FIG. 9 is a flow chart showing an example of a processing flow ofmeasurement of cardiac valve according to Example 2 hereof.

FIG. 10 is a diagram showing an example of contour modification bymanual correction or shape parameter adjustment according to Example 2hereof.

FIG. 11 is a flow chart showing an example of a processing flow ofextraction of cardiac mitral valve and aortic valve according to Example3 hereof.

FIG. 12 is a schematic diagram showing an example of contour extractionof cardiac mitral valve and aortic valve according to Example 3 hereof.

DESCRIPTION OF EMBODIMENTS

A variety of examples of the invention will be specifically described asbelow with reference to the accompanying drawings. Throughout thefigures illustrating the examples hereof, equal or similar referencenumerals are principally assigned to equal or similar components, whichare explained only once in most cases to avoid repetitions. It is notedthat feature points and a plurality of parts in the subject are definedto mean artificially set positions or regions of a subject organ such asheart, which are regarded as being anatomically meaningful. Out of thecontours of the plural parts in the subject, a contour of a portionwhere the parts contact each other is referred to as a boundary line.

Example 1

Example 1 illustrates an image processing device of an ultrasonicimaging system. The image processing device has a configuration where aprocessor acquires measurement information by taking the steps of:detecting feature points of a measurement object which are contained involume data acquired by transmitting/receiving an ultrasonic wave;extracting contours of plural parts of the measurement object based onthe detected feature points and anatomical definitions; and optimizingthe contours of the parts contacting each other (out of the detectedcontours of the plural parts) and combining together the plural parts soas to create a contour of the measurement object. Further, the exampleillustrates an image processing method of the image processing device.In this method, the image processing device acquires the measurementinformation by: detecting the feature points in the volume data of themeasurement object; extracting the contours of the plural parts of themeasurement object based on the detected feature points and theanatomical definitions; and optimizing the contours of the partscontacting each other (out of the detected contours of the plural parts)and combining together the plural parts so as to create the contour ofthe measurement object.

As shown in FIG. 1, for example, the ultrasonic imaging system ofExample 1 includes: an ultrasonic probe 7, an image generating portion107, and an image processing device 108. The ultrasonic probe 7transmits the ultrasonic wave to a subject 120 via a duplexer 101 andreceives an ultrasonic wave from the subject 120. The image generatingportion 107 generates an ultrasonic image from a signal received fromthe ultrasonic probe 7. The image processing device 108 receivesultrasonic volume data from the image generating portion 107 so as toprocess the received data as three-dimensional information of thesubject. The exemplary whole structure of the ultrasonic imaging systemshown in FIG. 1 is shared by other examples.

<System Configuration and Operations>

A detailed description is made as below on a specific configuration ofthe ultrasonic imaging system of the example. In addition to theultrasonic probe 7, the image generating portion 107 and the imageprocessing device 108 as shown in FIG. 1, the ultrasonic imaging systemof the example further includes: a transmitter 102, the duplexer 101, areceiver 105, a user interface (UI) 121 and a controller 106. Further,the ultrasonic imaging system is connected with a display 16 as an imagedisplay portion.

The transmitter 102 generates a transmission signal under control of thecontroller 106 and delivers the signal to each of the plural ultrasonicelements constituting the ultrasonic probe 7. This triggers the pluralultrasonic elements of the ultrasonic probe 7 to transmit ultrasonicwaves to the subject 120, respectively. The ultrasonic waves reflectedby the subject 120 go back to the plural ultrasonic elements of theultrasonic probe 7 where the ultrasonic waves are converted to electricsignals. The signals received by the ultrasonic elements are transmittedto the receiver 105 via the duplexer 101 while the receiver 105 delaysthe signals by predetermined delay amounts corresponding to receptionfocus points and adds the delayed signals. That is, the signals arephase-regulated and added. Such signal transmission and reception arerepeated for each of the plural reception focus points. The phased andadded signal is delivered to the image generating portion 107. Theduplexer 101 selectively connects the transmitter 102 or the receiver105 to the ultrasonic probe 7.

The image generating portion 107 generates an ultrasonic image as thevolume data by performing processing for receiving the phased and addedsignals from the receiver 105 and arranging the received signals atpositions corresponding to the reception focus points. The imageprocessing device 108 receives the volume data from the image generatingportion 107 and extracts standard sections. It is noted here that thestandard section is defined to mean a sectional image complying withguidelines for standard section acquisition. Although FIG. 1 shows thedisplay 16 located outside the system, the display 16 may also beincluded in the user interface 121 of the ultrasonic imaging system 100,as shown in FIG. 2.

Referring to an exemplary hardware configuration of the image processingdevice 108 and the user interface 121 shown in FIG. 2, a detaileddescription is made on the configuration and operations of the imageprocessing device 108 and user interface 121. Similarly to FIG. 1, theexemplary hardware configuration shown in FIG. 2 is shared by the otherexamples to be described hereinafter.

As shown in FIG. 2, the image processing device 108 includes: a centralprocessing unit (CPU) 1, a read only memory (ROM) 2, a random accessmemory (RAM) 3, a storage unit 4, and a display controller 15. The userinterface 121 includes: a medium input portion 11, an input controller13, an input device 14 and the display 16. The medium input portion 11,the input controller 13, the display controller 15 and the imagegenerating portion 107 are interconnected by means of a data bus 5 ofthe image processing device 108. The display controller 15 is connectedto the display 16 for control of display on the display 16. For example,the controller controllably drives the display 16 to display image datasuch as the standard section obtained by processing by the CPU 1.

At least one of the ROM2 and the RAMS is previously stored with anarithmetic processing program for the CPU1 and a variety of data pieceswhich are considered as necessary for implementation of the operationsof the image processing device 108. The various processes of the imageprocessing device 108, which will be described hereinafter, areimplemented by the CPU1 executing the previously stored program in atleast one of the ROM2 and the RAM3. Incidentally, the programs executedby the CPU1 may be previously stored in a storage medium 12 such as anoptical disk such that the medium input portion 11 such as an opticaldisk drive may read the program into the RAM3.

Further, the storage unit 4 may be previously stored with the programsuch that the program in the storage unit 4 may be loaded into the RAM3.Otherwise, the ROM2 may be previously stored with the program. Thestorage unit 4 includes an unillustrated shape model database. The shapemodel database includes average shapes of plural parts of a test objectsuch as cardiac valve of the subject, shape parameters of a principalcomponent and the like as information on the contours of anatomicalparts to be described hereinafter. The contour of the object isextracted by fitting the average shape in the database and the shapes ofthe principal components in the image.

The input device 14 of the user interface 121 is for receiving a useroperation and includes, for example, a keyboard, trackball, operationpanel, foot switch and the like. The input controller 13 receives anoperation instruction inputted by a user via the input device 14. Theoperation instruction received by the input controller 13 is processedand executed by the CPU1.

Next, the operations of the image processing device 108 of the exampleare described with reference to a flow chart of FIG. 3 showing the wholeprocessing flow of taking measurements of cardiac valve. The processingof the flow chart can be implemented by the CPU1 executing theabove-described programs.

First in Step 301 (hereinafter, written as S301), ultrasonic volume datagenerated by the image generating portion 107 is inputted.

In S302, feature points are detected from the inputted volume data. Aswill be described with reference to FIG. 4, the feature point means aposition artificially set on an object organ of the subject, asconsidered as anatomically meaningful. The position abounds ininformation on characteristic quantity present on a medical image and ishelpful in diagnosis. A machine learning technique based on positionalinformation of the image characteristic quantity and the feature pointto be described hereinafter is applied to the detection of the featurepoint.

In S303, the object organ is divided into plural parts based on theanatomical definitions and a contour of the respective parts isdetected. In a case where the object organ is a cardiac mitral valve,for example, the plural parts are six anatomical parts including lateralmargin of anterior cusp, a lateral margin of posterior cusp and thelike, as shown in FIG. 5 to be described hereinafter. Each of the partsis useful in diagnosis. A method based on a shape model, for example, isknown as a contour extraction method. The shape model is a whole seriesof vertices constituting an outline of an organ present on the medicalimage. As will be described with reference to FIG. 6, the shape modelincludes a profile model describing how an image feature value appearsaround a vertex, and a shape model describing shape variations.

Constructed profile models and shape models are previously stored in theshape model database in the storage unit 4. These models are retrievedsuch that the shape model is fitted in an image of an inputted unknownvolume data using the feature point detected in S302 as an initialposition. Next, the positions of the vertices are optimized based on therestriction in the image feature value by the profile model and therestriction in the shape by the shape model. The shape of the anatomicalpart can be extracted by repeating this process till all the verticesreach stable positions.

In S302, the contours of the parts that contact each other, out of theplurality of parts, namely the boundary lines are optimized. As will bedescribed hereinafter with reference to FIG. 7 and an expression 1, anoptimum boundary line is created by optimizing both of information on adistance from an unoptimized contour of the part to a created boundaryline and information on deviation between the created boundary line andthe average shape stored in the storage unit 4. The contours of theplural parts are defined by this optimization. The contour of the wholeorgan can be constructed from the resultant contours of the pluralparts.

In S305, measurements of the diagnostic items useful for the diagnosissuch as annulus diameter, valve height, and valvular area are takenbased on the created overall contour.

In S306, the CPU1 of the image processing device 108 outputs thecontours of the parts extracted in S303 (part contour extraction), thewhole contour reconstructed by the boundary line optimization in S304,and the measurement information of the annulus diameter, valve height,valvular area and the like as measured in S305, while the displaycontroller 15 transmits the outputs to the display 16 which displays theoutputs.

Next, a detailed description is made on the feature point detection inStep 302 of the example with reference to FIG. 4. FIG. 4 is a schematicdiagram showing an example of feature point setting in the case ofcardiac mitral valve. As indicated by round stamps in FIG. 4, positionsreplete with feature information, such as a central part 401 of leftannulus on an annular ring of mitral valve 400, an A1A2 joint 402, acentral part 403 of anterior cusp of valve ring, an A2A3 joint 404, acentral part 405 of right annular ring, a P1P2 joint 408, a left valvejoint 409, a right valve joint 410, an anterior valve cusp 411, and aposterior valve cusp 412, are set as the feature points. The featurepoint is set so as to roughly determine the initial shape and positionof each anatomical part.

Methods such as Hugh Forest and Support Vector Machine (SVM) are usedfor detection of the feature point. In a case where Hugh Forest is used,a decision tree is prepared for making decisions on details aboutdirection and distance between various particular regions in the volumedata such that a feature classifier capable of acquiring the directionand distance between arbitrary feature points from unknown volume datathe same way can be generated by combining a plurality of the decisiontrees. That is, when unknown volume data is inputted in the featureclassifier, vector information to the optimum retrieval feature pointcan be finally found by sequentially passing decision trees where thedirection and the positional relation of the inputted region image matchwith those of an object region.

Next, a detailed description is made on Step 303 of extraction of thecontours of plural parts according to the example. FIG. 5 shows anexample of defining the plural parts of the cardiac mitral valve basedon the anatomical definitions. As indicated by the dotted lines in FIG.5, the cardiac mitral valve is divided into six parts including: alateral margin of anterior cusp 501, a middle part of anterior cusp 502,an interior part of anterior cusp 503, a lateral margin of posteriorcusp 504, a middle part of posterior cusp 505, and an interior part ofposterior cusp 506. Respective shape model databases for the pluralparts are previously generated and stored in the storage unit 4. Theshape models are retrieved for the inputted unknown volume data so as toextract the contours of the respective parts.

A method based on well-known Active Shape Model (ASM) is used forcontour extraction. The shape model is a whole series of verticesconstituting an outline of an organ present on the medical image. FIG. 6is a diagram showing an example of contour model construction andcontour extraction in a case where the ASM method is used. The modelconsists of two parts. One part is a profile model 601 describing howthe image feature value appears at the periphery of a vertex, while theother part is a shape model 602 describing the shape variations.

The profile model 601 is for extraction of the image feature value basedon a method such as edge detection. The image feature value is extractedfrom a local region 604 of a vertex 603 defining the outline. The shapemodel 602 is constructed using Principal Component Analysis (PCA). Theshape model 602 includes an average shape and a shape principalcomponent vector representing a variation type. The average shape can bedetermined by calculating the average of all the shapes and construed asa feature that all the mitral valves have in common. The variation typeis determined by subtracting the average shape from each of all shapes,representing how much each shape varies from the average shape. Hence,the shape of a particular region is generated by choosing some variationtypes as bases and adding the average shape to the combination of thesebase values.

The contour extraction from the constructed profile model 601 and shapemodel 602 is performed as follows. The feature points detected in Step302 as represented by the hatched circles on the parts 501 to 506 inFIG. 5 are applied to the inputted unknown volume data for determinationof initial contour of the part. Next, the feature value of the vertexconstituting the outline is calculated based on the profile model 601. Amatching score of the profile model stored in the storage unit 4 thatmatches this feature value is calculated. Next, a curve functionincluding the vertex of the outline is fitted to a position of a highmatching score. Then, a new vertex position is obtained by optimizingthe curve function based on the shape restriction. The part contour 605can be extracted by repeating this processing till all the points reachthe stable points.

It is noted that in place of the above-described ASM method, well knownActive Appearance Model method, Constrained Local Model (CLM) method orthe like may also be applied to the shape extraction of the particularregion.

Now referring to FIG. 7, the description is made on an operation in theboundary line optimizing step 304 of the example shown in FIG. 3, or theoperation of optimizing boundary lines defining the contours of partscontacting each other, out of the plural parts extracted in Step 303.Since a part 701 and a part 702 contacting each other are extractedrespectively, boundary lines 703 and 704 defining the contours of thecontacting parts include portions not conforming to each other. Thisrequires the modification of the boundary lines by optimization in orderthat a contour of the whole body is generated from the contours of theplural parts. A boundary line optimization method of the exampleexpresses a minimization function ø(x) by using the following expression1, for example.

φ(X)=ε₁Σ_(i=1) ^(n)(P _(i) X _(i) +Q _(i) X _(i))+ε₂Σ_(i=1) ^(n) |X _(i)−S _(i)|  [Expression 1]

It is noted here that X=(X₁, X₂, . . . X_(n)) denotes a boundary line705 defining a contour of a portion where the parts contact each other;X_(i) denotes the i-th vertex on the boundary line 705; P_(i) denotesthe i-th vertex on the boundary line 703 of the part 701; Q_(i) denotesthe i-th vertex on the boundary line 704 of the part 702; P_(i)X_(i)denotes a distance between the vertex P_(i) and the vertex X_(i);Q_(i)X_(i) denotes a distance between the vertex Q_(i) and the vertexX_(i); S with bar above denotes an average shape of a boundary linecontacting the part 701 and the part 702, the average shape stored inthe storage unit; and 81, 82 denote weighting factors of distanceinformation and deviation from the average shape.

The first half of the expression 1 denotes information about distancesfrom the boundary line 705 to the boundary line 703 and to the boundaryline 704. The latter half of the expression 1 denotes shape informationindicating deviations of the boundary line 705 and the average shapestored by the storage unit 4. In this expression 1, the boundary line705 is updated by minimizing both the distance information in the firsthalf of the expression and the shape information in the latter half ofthe expression. An optimum boundary line 707 can be obtained byrepeating the processing till the function ø(x) reaches a value equal toa threshold value or less. Namely, out of the extracted contours of theplural parts, a processor of the image processing device 108 optimizesthe boundary lines defining the contours of the parts contacting eachother based on the distance information and shape information of thecontours of the parts contacting each other. A contour 706 of the wholemeasurement object including the plural parts can be created bycombining together the contours of the plural parts obtained byoptimizing the boundary lines.

FIG. 8 shows an example where the boundary lines defining the contoursof the parts contacting each other are modified by the boundary lineoptimization S304 and displayed on the display 16 in the deviceconfiguration of the example. The contours 801 of the plural partsdetected in S303 are displayed on a display screen. A whole contour 802is constructed from the contours 801 of the plural parts by the boundaryline optimization in S304. When, of the whole contour 802, a boundaryline 803 defining a contour of the parts that contact each other ismodified by the optimization in S304, a boundary line 804 and a boundaryline 805 of corresponding part contours are also modified and displayedconcurrently. Thus, the modifying motion can be displayed on the display16. After the boundary line optimization in S304, if it is determinedthat the boundary line needs correction, the user can correct theboundary line by manually dragging and dropping the boundary line with amouse of the input device 14. Further, if the boundary line 804 ismanually corrected, the image processing device 108 is adapted toperform processing for correcting the corresponding boundary line 805 aswell as the boundary line 803 in the whole contour in conjunction withthis correction and displays the results on the screen.

As just described, the processor of the image processing deviceaccording to the example displays the extracted contours of the pluralparts and the whole contour of the measurement object on the display asthe image display portion. Out of the extracted contours of the pluralparts, the processor also modifies the contours of the parts contactingeach other by optimizing the boundary lines defining the contours of theparts contacting each other and displays the modified contours on thedisplay. Further, when correcting one of the contours of the partscontacting each other, the processor also modifies the contour of theother one of the contacting parts in conjunction with the correction,and displays the modified contours on the display.

Next, measurement is taken on the items useful for diagnosis such asannulus diameter, valve height, and valvular area based on the extractedcontour. For instance, the annulus diameter means the maximum radiusbetween two points on the valve ring, while the annulus height means adistance between the highest point and the lowest point on a valve ringspline. Based on the created contour, the maximum diameter and area ofthe valve ring are automatically calculated. The extracted contour andthe measurement information including the measured annulus diameter,valve height, valvular area and the like are transmitted to the display16 for display purpose. As just described, the processor of the imageprocessing device is adapted to measure a distance between particularregions of the measurement object based on the contour of themeasurement object and to indicate the measurement information as themeasurement results on the display portion.

The ultrasonic imaging system of the example as described above isadapted to acquire the robust, high-precision contour and measurementinformation by taking the steps of: extracting, from thethree-dimensional information on the subject, the contours of the pluralparts based on the anatomical definitions of the measurement object;optimizing the boundary lines defining the contours of the partscontacting each other, out of the plural parts; and measuring thenecessary diagnostic items from the optimum contour.

Example 2

In the image processing device of the ultrasonic imaging system ofExample 1, Example 2 illustrates a configuration where if the userchecking the extracted contour on the screen determines that the contourneeds correction, the user can modify the contour by manual adjustmentor can semi-automatically modify the contour by way of shape parameteradjustment.

FIG. 9 is a flow chart showing the whole processing flow of takingcardiac valve measurements according to Example 2. In S901 to S904 ofthe figure, similarly to the processing flow of Example 1 shown in FIG.3, the whole contour is constructed from the contours of the parts bytaking the steps of: detecting the feature points from inputted valvevolume data; detecting the contours of plural parts based on thepositions of the feature points and the anatomical definitions; andoptimizing the boundary lines defining the contours of the partscontacting each other out of the detected plural parts. Subsequently inS905, the user checks the contour of a part displayed on an interfacescreen shown in FIG. 10 which will be described hereinafter. The userdetermines whether or not the contour needs correction.

If it is determined that the contour needs correction (YES), the contouris manually corrected via the interface or semi-automatically correctedby way of parameter adjustment or the like in S906 of FIG. 9. Thecontour obtained by the boundary line optimization in S904 is modifiedby this correction so that a proper contour of the measurement objectcan be extracted. On the other hand, if it is determined that thecontour does not need correction (NO), the operation flow proceeds tothe measurement of diagnostic items S907. The items are measured basedon the contour corrected in S906 or on the contour determined to need nocorrection. In S908, the measurement results are outputted to thedisplay 16 which can display the measurement results.

FIG. 10 shows an example of an interface for manual correction andsemi-automatic correction by way of parameter adjustment, the interfacedisplayed on the display 16 as the image display portion according tothe example. An interface 1000 includes: a part selection button 1001for selecting a part to be displayed; a display region 1002 fordisplaying a contour of an extracted part on a screen; a manualcorrection button 1003; a shape parameter adjustment control bar 1004used for semi-automatic correction; and a measurement value displayregion 1008. When the part selection button 1001 is selected, a selectedpart is highlighted just like a part selection button 1005.

The user can check a numerical value of a shape which is extracted anddisplayed at the measurement value display region 1008. If the shapeneeds correction, the user can manually make a fine adjustment of theshape. Specifically, when the user presses down the manual correctionbutton 1003, a previously stored manual correction program becomesexecutable on the CPU 1. The user consents to modification by draggingand dropping a desired region 1006 of a particular regional shape 1007displayed in the image display region 1002 so that the user can manuallycorrect a local contour of an area around the related region. Further,the whole shape can be adjusted by way of parameter adjustment. The usercan semi-automatically accomplish scaling, rotation, shape modificationand the like of a corresponding mitral valve by manipulating the controlbar 1004. Next, the size, area and the like of a region to be observedis calculated from the corrected contour 1002. These calculated valuesare redisplayed at the measurement value display region 1008 on thescreen of the interface 1000.

As just described, the image processing device of the example includesthe input portion such as the interface 1000 while the processormodifies the contours of the plural parts in response to a command tocorrect the contours of the plural parts inputted from the inputportion. The processor of the image processing device displays theparameter adjustment control bar in the image display portion andmodifies the contours of the plural parts in response to the correctioncommand by way of adjustment of the control bar. Further, the processorof the image processing device modifies the desired region inconjunction with the drag and drop of the desired region of the contoursof the plural parts shown at the display portion.

According to the example, more accurate contour can be extracted tosupport the measurement of the diagnostic items because the user checksthe extracted contour on the screen and if the contour needs correction,the user can correct the contour manually or semi-automatically by wayof adjustment of the shape parameters.

Example 3

In the image processing device of the ultrasonic imaging systemaccording to Examples 1 and 2, Example 3 illustrates a configurationwhere a contour of two or more adjoining organs, such as the mitralvalve and aortic valve, is wholly extracted so as to provide measurementinformation useful for diagnosis.

FIG. 11 is a flow chart showing an example of a processing flow ofextraction of cardiac mitral valve and aortic valve. In S1101, volumedata including the cardiac mitral valve and aortic valve is inputted. InS1102, feature points set on the mitral valve and aortic valve aredetected from the inputted valve volume data. Next, in S1103, the methodof Example 1 is used for dividing the mitral valve into plural parts andthe contours thereof are extracted. In S1104 of aortic valve contourextraction, the aortic valve is divided into plural parts based on theanatomical definitions and the contours thereof are extracted the sameway as in the method of Example 1. In S1105, boundary lines defining thecontours of the parts contacting each other, out of the extractedcontours of the mitral valve and aortic valve, are optimized the sameway as in S304 of Example 1. The whole contour of the combination of twoorgans including the mitral valve and aortic valve can be created byoptimizing the boundary lines. In the subsequent steps S1106 to S1109,similarly to the processing flow illustrated by the steps S905 to S908of Example 2, the user checks the extracted contours on the screen andif the contours need correction, the contours are modified by manualadjustment and by adjustment of shape parameters. In S1107, the itemsare measured based on the manually/semi-automatically corrected contoursor the contours determined to need no correction. In S1109 of outputtingmeasurement results, the measurement results are transmitted to thedisplay 16 which displays the measurement results.

FIG. 12 shows an example of the contour extraction of cardiac mitralvalve and aortic valve according to the example. In a mitral valvecontour 1201 extracted in S1103, and an aortic annulus contour 1202extracted in S1104, a boundary line 1204 of parts contacting each otheris optimized using the distance information or shape information thesame way as in S304 of Example 1. A whole contour 1203 can be extractedbased on the optimized contour of the two adjoining organs or the mitralvalve and the aortic valve.

It is noted that the invention is not limited to the foregoing examplesbut includes examples corresponding to a variety of organs. Theforegoing examples, for example, are the detailed illustrations toclarify the invention. The invention is not necessarily limited to whatincludes all the components described above. Some component of oneexample can be replaced by some component of another example. Further,some component of one example can be added to the arrangement of anotherexample. A part of the arrangement of each example permits addition ofsome component of another example, the omission thereof or replacementthereof.

The above-described components, functions, processors and the like havebeen described by way of the example where a program of implementing apart or all of the components, functions, processors and the like isgenerated and the CPU executes the program. It goes without saying thata part or all of the components, functions, processors and the like canbe implemented in a hardware by designing a part or all of thecomponents, functions, processors and the like in an integrated circuit,for example. Namely, all or a part of the functions of the imageprocessing device can be implemented in an integrated circuit such asASIC (Application Specific Integrated Circuit), FPGA (Field ProgrammableGate Array), and FPGA (Field Programmable Gate Array) in place of theprogram.

REFERENCE SIGNS LIST

-   -   1 . . . CPU,    -   2 . . . ROM,    -   3 . . . RAM,    -   4 . . . storage unit,    -   5 . . . bus,    -   7 . . . ultrasonic probe,    -   11 . . . medium input portion,    -   12 . . . storage medium,    -   13 . . . input controller,    -   14 . . . input device,    -   15 . . . display controller,    -   16 . . . display,    -   100 . . . ultrasonic imaging system,    -   101 . . . duplexer,    -   102 . . . transmitter,    -   105 . . . receiver,    -   106 . . . controller,    -   107 . . . image generating portion,    -   108 . . . image processing device,    -   120 . . . subject,    -   121 . . . user interface (UI),    -   601 . . . profile model,    -   602 . . . shape model,    -   701,702 . . . parts contacting each other,    -   703,704,804,805 . . . boundary lines defining contours of parts        contacting each other,    -   705,803 . . . boundary line,    -   706,802 . . . whole contour,    -   707, 1204 . . . optimized boundary line,    -   801 . . . contours of plural parts,    -   1000 . . . interface,    -   1001, 1005 . . . part selection button,    -   1002 . . . image display region,    -   1003 . . . manual correction button,    -   1004 . . . control bar,    -   1006 . . . region,    -   1007 . . . shape of particular region,    -   1008 . . . measurement value display region,    -   1201 . . . mitral valve contour,    -   1202 . . . aortic annulus contour,

1. An image processing device comprising a processor, wherein theprocessor detects feature points in volume data of a measurement object;extracts contours of a plurality of parts of the measurement objectbased on the detected feature points and anatomical definitions;optimizes the contours of parts contacting each other, out of theextracted contours of the plural parts, so as to combine together theplural parts for creating a contour of the measurement object; andacquires measurement information therefrom.
 2. The image processingdevice according to claim 1, wherein out of the extracted contours ofthe plural parts, the processor optimizes the contours of the partscontacting each other based on distance information and shapeinformation of the contours of the parts contacting each other.
 3. Theimage processing device according to claim 1, further comprising adisplay portion, wherein out of the extracted contours of the parts, theprocessor modifies the contours of the parts contacting each other byoptimizing the contours of the parts contacting each other; and displaysthe modified contours at the display portion.
 4. The image processingdevice according to claim 3, wherein the processor modifies one of thecontours of the parts contacting each other, concurrently modifying thecontour of the other one of the parts contacting each other; anddisplays the modified contours at the display portion.
 5. The imageprocessing device according to claim 3, wherein the processor displaysthe extracted contours of the plural parts and the contour of themeasurement object at the display portion.
 6. The image processingdevice according to claim 5, wherein the processor measures a distancebetween particular regions of the measurement object based on thecontour of the measurement object and displays the measurement resultsat the display portion.
 7. The image processing device according toclaim 5, further comprising an input portion, wherein the processormodifies the contours of the plural parts in response to an instructionfor correction of the contours of the plural parts as inputted from theinput portion.
 8. The image processing device according to claim 5,wherein the processor displays a control bar for parameter adjustment atthe display portion and modifies the contours of the plural parts inresponse to an instruction for correction by adjustment of the controlbar.
 9. The image processing device according to claim 5, wherein inresponse to a drag-and-drop operation for a desired region of thecontours of the plural parts displayed at the display portion, theprocessor modifies the contour of the desired region.
 10. An imageprocessing method for an image processing device, wherein the imageprocessing device detects feature points in volume data of a measurementobject; extracts contours of a plurality of parts of the measurementobject based on the detected feature points and anatomical definitions;optimizes the contours of parts contacting each other, out of theextracted contours of the plural parts, so as to combine together theplural parts for creating a contour of the measurement object; andacquires measurement information therefrom.
 11. The image processingmethod according to claim 10, wherein out of the extracted contours ofthe plural parts, the image processing device optimizes the contours ofthe parts contacting each other based on distance information and shapeinformation of the contours of the parts contacting each other.
 12. Theimage processing method according to claim 10, wherein the imageprocessing device includes a display portion, and out of the extractedcontours of the parts, the image processing device modifies the contoursof the parts contacting each other by optimizing the contours of theparts contacting each other and displays the modified contours at thedisplay portion.
 13. The image processing method according to claim 12,wherein the image processing device modifies one of the contours of theparts contacting each other, concurrently modifying the contour of theother one of the parts contacting each other and displays the modifiedcontours at the display portion.
 14. The image processing methodaccording to claim 12, wherein the image processing device displays theextracted contours of the plural parts and the contour of themeasurement object at the display portion.
 15. The image processingmethod according to claim 12, wherein the image processing devicemeasures a distance between particular regions of the measurement objectbased on the contour of the measurement object and displays themeasurement results at the display portion.